Extracting knowledge from text using SHELDON, a Semantic Holistic framEwork for LinkeD ONtology data

SHELDON1 is the first true hybridization of NLP machine reading and the Semantic Web. It extracts RDF data from text using a machine reader: the extracted RDF graphs are compliant to Semantic Web and Linked Data. It goes further and applies Semantic Web practices and technolo- gies to extend the current human-readable web. The input is represented by a sentence in any language. SHELDON includes different capabilities in order to extend machine reading to Semantic Web data: frame detection, topic ex- traction, named entity recognition, resolution and corefer- ence, terminology extraction, sense tagging and disambigua- tion, taxonomy induction, semantic role labeling, type in- duction, sentiment analysis, citation inference, relation and event extraction, nice visualization tools which make use of the JavaScript infoVis Toolkit and RelFinder. A demo of SHELDON can be seen and used at http://wit.istc.cnr. it/stlab-tools/sheldon.